NEOPOLIS AKADEMY
Zendesk RAG agent with knowledge base and memory
Advanced practical exercise to develop a Zendesk agent using RAG (retrieval-augmented generation) with a document base and memory. Integrates n8n, Supabase, PostgreSQL and OpenAI for retrieval, context and persistence.
View this course on Akademy ↗Enrolment and practical details are available on Neopolis Akademy.
What you will explore
Deploy a Zendesk agent using RAG: document indexing, contextual queries and augmented generation.
Technical architecture using n8n for orchestration, Supabase/PostgreSQL for storage and OpenAI for generation.
Emphasis on controls, fictional data and human validation to ensure safe, quality responses.
STEP BY STEP
Course programme
01Zendesk RAG agent with knowledge base and memory
Build a Zendesk RAG agent that connects a document store and conversational memory to enrich support answers. The practical focuses on environment setup, stepwise construction, and security checkpoints to ensure reliable integrations.
This practical guides you to integrate a RAG agent with Zendesk by connecting a document store (vector DB) and a conversational memory to improve answer relevance.
Start with environment setup (n8n, Supabase/PostgreSQL, AI APIs), then implement ingestion, embedding/indexing, retrieval and response orchestration within Zendesk flows.
The build is incremental: validate data access, retrieval quality and memory writes at each step to ensure predictable behaviour.
A security checkpoint covers access controls, API key handling and configuration practices to reduce data exposure in support workflows.
Explore this module on Akademy ↗Programme source: Neopolis Akademy. Original course page